Author

Weishu Zhao

Shanghai Jiao Tong UniversityORCID 0000-0002-0753-8300Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:proteomics· 2 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Aijun Jiang· 1 shared Banghao WuiD· 1 shared Bei‐Bei HeiD· 1 shared Bo WangiD· 1 shared Bozitao ZhongiD· 1 shared Changwei ShaoiD· 1 shared Chaodi Kong· 1 shared Chaolun LiiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBioinformatics

Aijun Jiang

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2 papers

Recent·Most cited

The genetic repertoire of the deep sea: from sequence to structure and function

Yang Guo, Zongan Wang, Denghui Li, Lele Wang, Hongxia Lan, Fei Guo, Ziyu Zhao, Zhenjun Liu, Liang Meng, Xuechun Shen, Minxiao Wang, Weishu Zhao, Weijia Zhang, Chaodi Kong, Liuxin Shi, , Yuliang Dong

This study analyzes the genetic diversity of the deep sea, linking protein structures to genetic variants and identifying biotechnologically relevant features.

Cell Host & Microbe · Jun 10, 2026Peer-reviewedBioinformatics

Deep learning-guided design of hydrolases for crystalline PET depolymerization

Banghao Wu, Mingchen Li, J C Zhang, Li J, Xuling Wang, Bozitao Zhong, J S Liu, Yunjie Liu, Tan Yang, Tan Yang, Wei Dong Qi, Pan Tan, Weishu Zhao, Lirong Zheng, Liang Hong

This paper designs an engineered PET hydrolase, VenusPETase, using deep learning to enhance PET depolymerization efficiency and thermostability, achieving high TPA yields and complete degradation of commercial PET.

bioRxiv · Jun 5, 2026 · PreprintBiochemistry